Triple

T21340727
Position Surface form Disambiguated ID Type / Status
Subject North Bohemia E526182 entity
Predicate hasCity P316 FINISHED
Object Děčín NE NERFINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Děčín | Statement: [North Bohemia, hasCity, Děčín]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Děčín
Context triple: [North Bohemia, hasCity, Děčín]
  • A. Děčín chosen
    Děčín is a city in the north of the Czech Republic known as a gateway to the scenic Elbe Sandstone Mountains and Bohemian Switzerland National Park.
  • B. Žatec
    Žatec is a historic Czech town in the Ústí nad Labem Region renowned for its long-standing hop-growing tradition and beer production.
  • C. Pardubice
    Pardubice is a city in the Czech Republic known for its ice hockey tradition, historic center, and as the hometown of legendary NHL goaltender Dominik Hašek.
  • D. Liberec
    Liberec is a city in the northern Czech Republic known for its textile industry heritage, mountainous surroundings, and the landmark Ještěd Tower.
  • E. Chrudim
    Chrudim is a historic town in the Pardubice Region of the Czech Republic, known for its well-preserved medieval center and cultural heritage.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69e0b51c33048190ab27cede74ef798c completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e8a84dfa04819097dbe21eb40a45ef completed April 22, 2026, 10:51 a.m.
Created at: April 16, 2026, 4:44 p.m.